Survey of useful functions

Analyzing Business Data in SQL

Michel Semaan

Data Scientist

Dealing with dates

DATE_TRUNC('quarter', '2018-08-13') ? '2018-07-01 00:00:00+00:00'
'2018-07-01 00:00:00+00:00' :: DATE ? '2018-07-01'

Dates in reports

Human-readable dates are important in reporting
The default date format, '2018-08-13', isn't very readable
How do you get from '2018-08-13' to 'Friday 13, August 2018'?

Solution

TO_CHAR('2018-08-13', 'FMDay DD, FMMonth YYYY') ? 'Friday 13, August 2018'

TO_CHAR()

TO_CHAR(DATE, TEXT) ? TEXT (the formatted date string)
Example: Dy ? Abbreviated day name (Mon, Tues, etc.)
- TO_CHAR('2018-06-01', 'Dy') ? 'Fri'
- TO_CHAR('2018-06-02', 'Dy') ? 'Sat'
Patterns in the format string will be replaced by what they represent in the date; other characters remain as-is
Example: DD ? Day number (01 - 31)
- TO_CHAR('2018-06-01', 'Dy - DD') ? 'Fri - 01'
- TO_CHAR('2018-06-02', 'Dy - DD') ? 'Sat - 02'

Pattern	Description
`FMDay`	Full day name (`Monday`, `Tuesday`, etc.)
`MM`	Month of year (`01` - `12`)
`Mon`	Abbreviated month name (`Jan`, `Feb`, etc.)
`FMMonth`	Full month name (`January`, `February`, etc.)
`YY`	Last 2 digits of year (`18`, `19`, etc.)
`YYYY`	Full 4-digit year (`2018`, `2019`, etc.)

Documentation: https://www.postgresql.org/docs/9.6/functions-formatting.html

Query

SELECT DISTINCT
  order_date,
  TO_CHAR(order_date,
          'FMDay DD, FMMonth YYYY') AS format_1,
  TO_CHAR(order_date,
          'Dy DD Mon/YYYY') AS format_2
FROM orders
ORDER BY order_date ASC
LIMIT 3;

Result

order_date  format_1                format_2       
----------  ----------------------  ---------------
2018-06-01  Friday 01, June 2018    Fri 01/Jun 2018
2018-06-02  Saturday 02, June 2018  Sat 02/Jun 2018
2018-06-02  Sunday 03, June 2018    Sun 03/Jun 2018

Window functions revisited

SUM(...) OVER (...): Calculates a column's running total
- Example: SUM(registrations) OVER (ORDER BY registration_month) calculates the registrations running total
LAG(...) OVER (...): Fetches a preceding row's value
- Example: LAG(mau) OVER (ORDER BY active_month) returns the previous month's active users (MAU)
RANK() OVER (...): Assigns a rank to each row based on that row's position in a sorted order
- Example: RANK() OVER (ORDER BY revenue DESC) ranks users, eateries, or months by the revenue they've generated

Query

SELECT
  user_id,
  SUM(meal_price * order_quantity) AS revenue
FROM meals
JOIN orders ON meals.meal_id = orders.meal_id
GROUP BY user_id
ORDER BY revenue DESC
LIMIT 3;

Result

user_id  revenue
-------  -------
18       626
76       553.25
73       537

Query

WITH user_revenues AS (
  SELECT
    user_id,
    SUM(meal_price * order_quantity) AS revenue
  FROM meals
  JOIN orders ON meals.meal_id = orders.meal_id
  GROUP BY user_id)

SELECT
  user_id,
  RANK() OVER (ORDER BY revenue DESC)
    AS revenue_rank
FROM user_revenues
ORDER BY revenue_rank DESC
LIMIT 3;

Result

user_id  revenue_rank
-------  ------------
18       1
76       2
73       3

Survey of useful functions

Analyzing Business Data in SQL